Databases

Question 1

Structured Data

Answer 1

data is often organized to support transactional and analytical applications. Structured data is most commonly stored in relational databases but can also be stored in non-relational databases.

Question 2

Unstructured Data

Answer 2

data is not organized in any distinguishable or predefined manner. Common stores for unstructured data are non-relational key-value databases. Unstructured data is full of irrelevant information, which means data needs to first be processed to perform any kind of meaningful analysis

Question 3

Semistructured

Answer 3

data can be just as predictable and organized as structured data. The difference is that semistructured data is flexible and can be updated without the requirement to change the schema for every single record in a table. non-relational stores

Question 4

OLAP

Answer 4

Relational DB online Transactional Processing. Optimize for Read

Question 5

OLTP

Answer 5

Relational DB Online Transaction Processing. Optimize for Write

Question 6

Aurora

Answer 6

Aurora is MySQL and PostgreSQL compatible.

log structured distributed storage layer

auto 6 copies of data across AZs
backed up to S3 with snapshots
serverless

Question 7

Redshift

Answer 7

Amazon Redshift delivers 10 times faster performance than other data warehouses by using machine learning, massively parallel query execution, and columnar storage on high-performance disk. You can set up and deploy a new data warehouse in minutes. Run queries across petabytes of data in your Amazon Redshift data warehouse and exabytes of data directly from your data lake built on Amazon Simple Storage Service (Amazon S3) with Amazon Redshift Spectrum.

Question 8

Steps to create RDS

Answer 8

1. VPC
2. Subnets (requires 2 in 2 different AZs)
3. EC2
4. Security Group

Question 9

Aurora

Answer 9

1. DB Instance Class (mem optimized or burstable)
   2

Question 10

Foreign Key

Answer 10

Used to create relationships between tables in a relational database

Question 11

updating the schema

Answer 11

Adding a column in a nonelational db is not required to update. Relational update is required.

Question 12

T/F Nonrelational databases are optimized for storage?

Answer 12

False: they are optimized for compute.

Question 13

Which DB type scales vertically

Answer 13

Relational

Question 14

T/F both types of DB use OLTP and OLAP?

Answer 14

Flase. Only relations uses OLAP

Question 15

Key Value

Answer 15

Uses in Non-relational
Typicall stored in one table.
Can handle varied data
flexible

Question 16

Document DBs

Answer 16

Uses Non relations
Python and Node.js
elements are person, place or thing.Mongo DB key word

Question 17

In-Memory DB

Answer 17

Real time access to data
nonrelational
frequently accesses not frequently updated
cacheing gaming and session stortes

Question 18

Graphy DB

Answer 18

Nonrelational
store data as nodes
visualize data

Question 19

Elasticach for intensive apps

Answer 19

Amazon ElastiCache to support data-intensive apps or improve the performance of your existing apps by retrieving data from high throughput and low latency in-memory data stores. This service offers fully managed Redis and Memcached cache engines for in-memory data stores. ElastiCache is a popular choice for gaming, advertising technology (ad tech), financial service, healthcare, and Internet of Things (IoT) apps.

Question 20

Redis and Inmemory

Answer 20

” elasticache key word” Uses as noralational engines for quick acces to data

Question 21

Amazon DynamoDB

Answer 21

can handle more than 10 trillion requests per day and support peaks of more than 20 million requests per second. More than 100,000 AWS customers have chosen DynamoDB as their key-value and document store database for mobile, web, gaming, ad tech, IoT, and other applications that need low-latency data access at any scale. DynamoDB supports ACID-compliant transactions

uses partition keys for table and can use sort keys for sort

If no sort keys primary key and partition are the same.

billed for each read and write

Question 22

Neptune

Answer 22

fully managed graph database service that makes it easy to build and run applications that work with highly connected data sets used to discover potential fraudulent behavior before it happens. This starts with finding interactions between products, locations, and devices and then mapping those data points to individual users, customers, and/or employees.

Neptune graph use cases include recommendation engines, fraud detection, knowledge graphs, drug discovery, and network security.

Can be structured, semistructured, or unstructured.

Question 23

Amazon DocumentDB

Answer 23

reliable, and fully managed database service that allows you to set up, operate, and scale MongoDB-compatible databases in the cloud. With Amazon DocumentDB, you can run the same application code and use the same drivers and tools that you use with MongoDB.

Semistructured data

Question 24

RDS security groups facts

Answer 24

They don’t exist. Use DB security groups.

Question 25

What are clustered indexes used with

Answer 25

Relational DBs only or document DB

Question 26

heterogeneous migration

Answer 26

Heterogeneous migrations, where you migrate between different database engines, requires use of the AWS Schema Conversion Tool (AWS SCT) to translate your database schema to the new platform.

Question 27

Redshift comprised of

Answer 27

Amazon Redshift clusters are comprised of nodes. Compute nodes divide work among slices. Each slice is assigned a portion of the node’s memory and drive space. When you connect to an Amazon Redshift cluster, you use the SQL endpoint.

There are only two types of nodes in Amazon Redshift: a single leader node and one or more compute nodes. Amazon Redshift cannot use OLE DB drivers.

Question 28

Document DB

Answer 28

Amazon DocumentDB clusters can only be run in an Amazon VPC. Amazon DocumentDB decouples storage and compute, enabling each to scale independently. All instances within the cluster support data reads.

The basic component of Amazon DocumentDB is the cluster, which contains a storage volume and instances. Once the cluster is provisioned, you can add and remove instances as needed.

Stores data in Json forms and semistructured documents

Question 29

Benefits of Document DB

Answer 29

Flexible indexing (Correct)
Ad-hoc querying (Correct)
Powerful analytics (Correct)